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Curriculum
Curriculum
A four-year, English-medium curriculum designed to build AI competency progressively from foundations to advanced applications and capstone projects.
Credit Requirements
As an interdisciplinary major, Applied Artificial Intelligence can be pursued as a primary major, double major, or minor. Credit requirements follow the Dongseo University Academic Regulations (Article 28), with the program offering 78 total credits across 24 courses from which students select according to their chosen track.
60
Primary Major
credits required
credits required
36
Double Major
credits required
credits required
18
Minor
credits required
credits required
78
Total Offered
credits available
credits available
Key Notes
- All Applied AI courses are offered as major electives (no required courses).
- When a course in this program overlaps with the student's primary major, credits may be recognized for both, up to 12 credits for double major and 6 credits for minor.
- Primary major students follow general degree requirements of 120 total credits for graduation, including liberal arts (30) and major coursework (60).
- Specific selection criteria, quotas, and procedures are determined by the program's Curriculum Committee.
Enrollment Information
Applied Artificial Intelligence enrollment follows the university-wide schedule for interdisciplinary majors.
| Item | Details |
|---|---|
| Eligibility | Currently enrolled undergraduate students from the second year onward. |
| Application Period | Mid-July and mid-January, in line with the university academic calendar. |
| Available Tracks | Primary Major, Double Major, or Minor. |
| Withdrawal | Students who wish to withdraw must submit a withdrawal form to the Academic Affairs Team (4F, New Millennium Building). Courses already taken are recognized as electives or as primary major credits where applicable. |
| Academic Advising | Students must consult with their academic advisor before applying to ensure the chosen track aligns with their primary major and graduation plan. The advisor will guide students through eligibility, course selection, and credit recognition. |
Curriculum Structure
The curriculum follows a vertical progression from foundations to applications to specialization, ensuring students develop core competencies through repeated exposure across academic years.
Year 1 — Programming Foundations
Introductory programming and computational thinking to prepare students from diverse academic backgrounds.
| Course Title | Year/Sem | Credits | Theory/Practice |
|---|---|---|---|
| Advanced Programming | 1/2 | 3 | 1 / 2 |
Year 2 — Core Computer Science & Mathematics
Foundational coursework in algorithms, data structures, databases, networks, and the mathematical underpinnings of AI.
| Course Title | Year/Sem | Credits | Theory/Practice |
|---|---|---|---|
| Introduction to Linear Algebra | 2/1 | 3 | 2 / 1 |
| Web Programming | 2/1 | 3 | 1 / 2 |
| Data Structure | 2/1 | 3 | 2 / 1 |
| Computer Network Programming | 2/1 | 3 | 2 / 1 |
| Introduction to Databases | 2/2 | 3 | 2 / 1 |
| Object Oriented Programming | 2/2 | 3 | 1 / 2 |
| Software Design | 2/2 | 3 | 2 / 1 |
| Operating System | 2/2 | 3 | 2 / 1 |
Year 3 — AI Application & Cloud
Core AI coursework covering machine learning, deep learning, big data, and cloud-based AI deployment.
| Course Title | Year/Sem | Credits | Theory/Practice |
|---|---|---|---|
| Algorithm | 3/1 | 3 | 2 / 1 |
| Artificial Intelligence | 3/1 | 3 | 2 / 1 |
| Advanced Web Programming | 3/1 | 3 | 1 / 2 |
| Big Data Analysis and Modeling | 3/1 | 3 | 1 / 2 |
| Introduction to Cloud Computing | 3/2 | 3 | 2 / 1 |
| Deep Learning Foundations Capstone | 3/2 | 3 | 2 / 1 |
| Server Programming | 3/2 | 3 | 1 / 2 |
| Advanced Database | 3/2 | 3 | 1 / 2 |
Year 4 — Specialization & Capstone
Advanced AI topics, computer vision, research methods, and capstone projects culminating in a portfolio and bachelor thesis.
| Course Title | Year/Sem | Credits | Theory/Practice |
|---|---|---|---|
| Bachelor Thesis 1 | 4/1 | 4 | 2 / 2 |
| Research Methods | 4/1 | 3 | 2 / 1 |
| Advanced Artificial Intelligence | 4/1 | 3 | 1 / 2 |
| Foundations of Computer Vision Capstone | 4/1 | 2 | 1 / 1 |
| Bachelor Thesis 2 | 4/2 | 4 | 2 / 2 |
| Portfolio | 4/2 | 8 | 4 / 4 |
| AI Essentials Workshop | 4/2 | 3 | 1 / 2 |